The purpose of the research was to determine whether there is a statistically significant relationship or correlation between the quantity of COVID-19 instances per million and GDP per capita average life expectancy. The study used data from 174 countries obtained from the World Data Bank website for the period 2019-2020. According to descriptive findings, there were an average of 222,158,9146 coronavirus cases during the time period, with cases ranging in number from 15.12 to 941,125.25. The range of the mean GDP per capita in 2020–2021 was 161,491.3528, the range of the mean life expectancy was 72.38786127, and the range of the mean GDP per capita was 53.25–84.63. The results of the correlation analysis revealed a strong correlation between the number of cases per million and average life expectancy (correlation coefficient = 0.541) and a moderately positive correlation between the number of cases per million and GDP per capita (correlation coefficient = 0.415). Regression analysis was also employed in the study to examine the statistical significance of these connections. The data provided did not include the regression analysis's findings. The findings of the study can help policymakers and public health officials make informed decisions about how to allocate resources and respond to the pandemic. For example, the strong correlation between COVID-19 cases and life expectancy suggests that countries with lower life expectancies may be more vulnerable to the virus, and targeted interventions may be needed in these areas to prevent further spread. Additionally, the moderately positive correlation between COVID-19 cases and GDP per capita suggests that economic factors may play a role in the pandemic's spread, and policymakers may need to consider economic support measures alongside public health measures to combat the virus effectively. Overall, this research provides valuable insights into the complex interplay between COVID-19, public health, and economic factors.